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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411
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        Tool Citations

        Please remember to cite the tools that you use in your analysis.

        To help with this, you can download publication details of the tools mentioned in this report:

        About MultiQC

        This report was generated using MultiQC, version 1.27.1

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        This report has been generated by the genotoul-bioinfo/metagwgs analysis pipeline. For information about how to interpret these results, please see the documentation.
        Report generated on 2025-12-12, 02:52 CET based on data in: /data/users/fkurz/metagenomics/output_hifiasm_01/work/ce/923f59fac207d76dcbebe31dba6c5d

        General Statistics

        Showing 48/48 rows and 10/20 columns.
        Sample NameDupsGCAvg lenMedian lenFailedSeqsN50 (Kbp)Assembly Length (Mbp)ReadsReads mapped% Reads mappedN50 (Kbp)Assembly Length (Mbp)ReadsReads mapped% Reads mappedOrganismContigsBasesCDS
        bc2121
        1.3%
        71.0%
        8494bp
        7499bp
        10%
        0.4M
        210.4Kbp
        66.4Mbp
        0.4M
        0.4M
        99.3%
        0.4M
        0.4M
        99.3%
        NA
        644
        66363466
        63063
        bc2121_select_contigs_size1000
        210.4Kbp
        66.4Mbp
        bc2122
        0.4%
        66.0%
        8548bp
        7499bp
        10%
        0.4M
        232.0Kbp
        210.9Mbp
        0.4M
        0.4M
        97.8%
        0.4M
        0.4M
        97.8%
        NA
        2121
        210922174
        201900
        bc2122_select_contigs_size1000
        232.0Kbp
        210.9Mbp
        bc2123
        0.6%
        67.0%
        9148bp
        8499bp
        10%
        0.4M
        3909.4Kbp
        64.9Mbp
        0.4M
        0.4M
        98.7%
        0.4M
        0.4M
        98.7%
        NA
        462
        64902627
        59857
        bc2123_select_contigs_size1000
        3909.4Kbp
        64.9Mbp
        bc2124
        0.5%
        57.0%
        8919bp
        8499bp
        10%
        0.3M
        191.6Kbp
        140.9Mbp
        0.3M
        0.3M
        98.9%
        0.3M
        0.3M
        98.9%
        NA
        1456
        140863752
        133496
        bc2124_select_contigs_size1000
        191.6Kbp
        140.9Mbp
        bc2125
        1.4%
        51.0%
        5172bp
        4499bp
        20%
        0.7M
        2300.4Kbp
        92.6Mbp
        0.7M
        0.7M
        99.8%
        0.7M
        0.7M
        99.8%
        NA
        192
        92566542
        82774
        bc2125_select_contigs_size1000
        2300.4Kbp
        92.6Mbp
        bc2126
        1.3%
        49.0%
        6066bp
        5499bp
        20%
        0.8M
        2022.5Kbp
        114.6Mbp
        0.8M
        0.8M
        99.3%
        0.8M
        0.8M
        99.3%
        NA
        3039
        114569058
        92439
        bc2126_select_contigs_size1000
        2022.5Kbp
        114.6Mbp
        bc2127
        1.0%
        49.0%
        7015bp
        6499bp
        20%
        0.8M
        3820.7Kbp
        128.9Mbp
        0.8M
        0.8M
        99.2%
        0.8M
        0.8M
        99.2%
        NA
        4546
        128910244
        106747
        bc2127_select_contigs_size1000
        3820.7Kbp
        128.9Mbp
        bc2128
        1.5%
        47.0%
        6473bp
        6499bp
        20%
        0.6M
        2109.1Kbp
        92.4Mbp
        0.6M
        0.6M
        98.5%
        0.6M
        0.6M
        98.5%
        NA
        3085
        92386496
        75479
        bc2128_select_contigs_size1000
        2109.1Kbp
        92.4Mbp
        bc2161
        0.4%
        62.0%
        10379bp
        9499bp
        10%
        0.3M
        4346.0Kbp
        105.9Mbp
        0.3M
        0.3M
        98.8%
        0.3M
        0.3M
        98.8%
        NA
        499
        105928087
        99076
        bc2161_select_contigs_size1000
        4346.0Kbp
        105.9Mbp
        bc2162
        0.3%
        66.0%
        8966bp
        8499bp
        10%
        0.3M
        276.7Kbp
        181.9Mbp
        0.3M
        0.3M
        96.5%
        0.3M
        0.3M
        96.5%
        NA
        2002
        181866166
        173738
        bc2162_select_contigs_size1000
        276.7Kbp
        181.9Mbp
        bc2163
        1.8%
        49.0%
        9016bp
        8499bp
        10%
        0.6M
        175.0Kbp
        76.8Mbp
        0.6M
        0.5M
        98.9%
        0.6M
        0.5M
        98.9%
        NA
        826
        76848011
        74687
        bc2163_select_contigs_size1000
        175.0Kbp
        76.8Mbp
        bc2164
        0.7%
        61.0%
        9746bp
        8499bp
        10%
        0.4M
        351.1Kbp
        65.2Mbp
        0.4M
        0.3M
        98.6%
        0.4M
        0.3M
        98.6%
        NA
        605
        65247350
        62961
        bc2164_select_contigs_size1000
        351.1Kbp
        65.2Mbp
        bc2165
        0.4%
        56.0%
        9835bp
        9499bp
        10%
        0.4M
        2802.4Kbp
        102.4Mbp
        0.4M
        0.4M
        98.3%
        0.4M
        0.4M
        98.3%
        NA
        795
        102422094
        97048
        bc2165_select_contigs_size1000
        2802.4Kbp
        102.4Mbp
        bc2166
        0.4%
        52.0%
        10179bp
        9499bp
        10%
        0.3M
        207.1Kbp
        154.9Mbp
        0.3M
        0.3M
        98.0%
        0.3M
        0.3M
        98.0%
        NA
        1351
        154921777
        141895
        bc2166_select_contigs_size1000
        207.1Kbp
        154.9Mbp
        bc2167
        0.9%
        61.0%
        9207bp
        8499bp
        10%
        0.5M
        3081.6Kbp
        66.0Mbp
        0.5M
        0.5M
        99.2%
        0.5M
        0.5M
        99.2%
        NA
        543
        65950107
        62053
        bc2167_select_contigs_size1000
        3081.6Kbp
        66.0Mbp
        bc2168
        1.8%
        47.0%
        3714bp
        3499bp
        30%
        0.6M
        4074.7Kbp
        40.1Mbp
        0.6M
        0.6M
        96.4%
        0.6M
        0.6M
        96.4%
        NA
        264
        40085885
        35615
        bc2168_select_contigs_size1000
        4074.7Kbp
        40.1Mbp
        bc2169
        0.2%
        65.0%
        8893bp
        8499bp
        20%
        0.4M
        575.3Kbp
        247.8Mbp
        0.4M
        0.4M
        96.5%
        0.4M
        0.4M
        96.5%
        NA
        2320
        247830322
        239278
        bc2169_select_contigs_size1000
        575.3Kbp
        247.8Mbp
        bc2170
        0.5%
        57.0%
        9663bp
        8499bp
        10%
        0.4M
        244.5Kbp
        71.0Mbp
        0.4M
        0.4M
        97.8%
        0.4M
        0.4M
        97.8%
        NA
        726
        70971502
        68402
        bc2170_select_contigs_size1000
        244.5Kbp
        71.0Mbp
        bc2171
        0.6%
        62.0%
        11117bp
        10499bp
        0%
        0.4M
        473.9Kbp
        133.0Mbp
        0.4M
        0.4M
        98.0%
        0.4M
        0.4M
        98.0%
        NA
        1066
        133039126
        128156
        bc2171_select_contigs_size1000
        473.9Kbp
        133.0Mbp
        bc2172
        0.7%
        48.0%
        5397bp
        5499bp
        20%
        0.3M
        2117.9Kbp
        79.9Mbp
        0.3M
        0.3M
        98.6%
        0.3M
        0.3M
        98.6%
        NA
        1275
        79936471
        72143
        bc2172_select_contigs_size1000
        2117.9Kbp
        79.9Mbp
        bc2173
        0.4%
        52.0%
        10961bp
        10499bp
        10%
        0.4M
        477.2Kbp
        138.5Mbp
        0.4M
        0.4M
        98.5%
        0.4M
        0.4M
        98.5%
        NA
        1039
        138506351
        131371
        bc2173_select_contigs_size1000
        477.2Kbp
        138.5Mbp
        bc2174
        0.3%
        69.0%
        8989bp
        7499bp
        10%
        0.3M
        4256.8Kbp
        85.0Mbp
        0.3M
        0.3M
        97.9%
        0.3M
        0.3M
        97.9%
        NA
        235
        85041923
        74691
        bc2174_select_contigs_size1000
        4256.8Kbp
        85.0Mbp
        bc2175
        0.6%
        46.0%
        3205bp
        3249bp
        30%
        0.1M
        648.2Kbp
        29.4Mbp
        0.1M
        0.1M
        81.3%
        0.1M
        0.1M
        81.3%
        NA
        97
        29356424
        25787
        bc2175_select_contigs_size1000
        648.2Kbp
        29.4Mbp
        bc2176
        1.6%
        46.0%
        3996bp
        3499bp
        20%
        0.6M
        4075.7Kbp
        37.8Mbp
        0.6M
        0.6M
        99.3%
        0.6M
        0.6M
        99.3%
        NA
        80
        37845507
        33334
        bc2176_select_contigs_size1000
        4075.7Kbp
        37.8Mbp

        FastQC (raw)

        Version: 0.12.1

        Quality control tool for high throughput sequencing data.URL: http://www.bioinformatics.babraham.ac.uk/projects/fastqc

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        Created with MultiQC

        Sequence Quality Histograms

        The mean quality value across each base position in the read.

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

        Created with MultiQC

        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

        Created with MultiQC

        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called.

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample row to see a line plot for that dataset.
        Rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

        Created with MultiQC

        Per Base N Content

        The percentage of base calls at each position for which an N was called.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

        Created with MultiQC

        Sequence Length Distribution

        The distribution of fragment sizes (read lengths) found. See the FastQC help

        Created with MultiQC

        Sequence Duplication Levels

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (e.g. PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

        Created with MultiQC

        Overrepresented sequences by sample

        The total amount of overrepresented sequences found in each library.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as overrepresented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        24 samples had less than 1% of reads made up of overrepresented sequences

        Top overrepresented sequences

        Top overrepresented sequences across all samples. The table shows 20 most overrepresented sequences across all samples, ranked by the number of samples they occur in.

        Showing 1/1 rows and 3/3 columns.
        Overrepresented sequenceReportsOccurrences% of all reads
        CAGCCCATAGCACTTGTCCTTCGTTCCCAATTTAGGGAATGGCGTTTGTG
        1
        1182
        0.0113%

        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

        Created with MultiQC

        Status Checks

        Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

        Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

        In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

        Created with MultiQC

        Quast primary assembly

        This section of the report shows primary assembly metrics.URL: http://quast.bioinf.spbau.ruDOI: 10.1093/bioinformatics/btt086

        Assembly Statistics

        Showing 24/24 rows and 4/4 columns.
        Sample NameN50 (Kbp)L50 (K)Largest contig (Kbp)Length (Mbp)
        bc2121
        210.4Kbp
        0.1K
        8237.0Kbp
        66.4Mbp
        bc2122
        232.0Kbp
        0.1K
        8223.6Kbp
        210.9Mbp
        bc2123
        3909.4Kbp
        0.0K
        8224.0Kbp
        64.9Mbp
        bc2124
        191.6Kbp
        0.1K
        8294.3Kbp
        140.9Mbp
        bc2125
        2300.4Kbp
        0.0K
        6917.0Kbp
        92.6Mbp
        bc2126
        2022.5Kbp
        0.0K
        8226.3Kbp
        114.6Mbp
        bc2127
        3820.7Kbp
        0.0K
        9351.0Kbp
        128.9Mbp
        bc2128
        2109.1Kbp
        0.0K
        8217.1Kbp
        92.4Mbp
        bc2161
        4346.0Kbp
        0.0K
        8227.5Kbp
        105.9Mbp
        bc2162
        276.7Kbp
        0.1K
        7823.1Kbp
        181.9Mbp
        bc2163
        175.0Kbp
        0.0K
        8228.8Kbp
        76.8Mbp
        bc2164
        351.1Kbp
        0.0K
        5858.1Kbp
        65.2Mbp
        bc2165
        2802.4Kbp
        0.0K
        8230.3Kbp
        102.4Mbp
        bc2166
        207.1Kbp
        0.1K
        10953.7Kbp
        154.9Mbp
        bc2167
        3081.6Kbp
        0.0K
        5617.2Kbp
        66.0Mbp
        bc2168
        4074.7Kbp
        0.0K
        6909.6Kbp
        40.1Mbp
        bc2169
        575.3Kbp
        0.0K
        7026.6Kbp
        247.8Mbp
        bc2170
        244.5Kbp
        0.0K
        6974.4Kbp
        71.0Mbp
        bc2171
        473.9Kbp
        0.0K
        5792.8Kbp
        133.0Mbp
        bc2172
        2117.9Kbp
        0.0K
        6917.9Kbp
        79.9Mbp
        bc2173
        477.2Kbp
        0.0K
        7025.3Kbp
        138.5Mbp
        bc2174
        4256.8Kbp
        0.0K
        8282.7Kbp
        85.0Mbp
        bc2175
        648.2Kbp
        0.0K
        1886.7Kbp
        29.4Mbp
        bc2176
        4075.7Kbp
        0.0K
        6945.4Kbp
        37.8Mbp

        Number of Contigs

        This plot shows the number of contigs found for each assembly, broken down by length.

        Created with MultiQC

        Reads alignment on unfiltered assembly

        This section reports reads alignement on contigs.URL: http://www.htslib.orgDOI: 10.1093/bioinformatics/btp352

        Flagstat

        This module parses the output from samtools flagstat

        Created with MultiQC

        Quast filtered assembly

        This section of the report shows metrics of the filtered assemblies.URL: http://quast.bioinf.spbau.ruDOI: 10.1093/bioinformatics/btt086

        Assembly Statistics

        Showing 24/24 rows and 4/4 columns.
        Sample NameN50 (Kbp)L50 (K)Largest contig (Kbp)Length (Mbp)
        bc2121_select_contigs_size1000
        210.4Kbp
        0.1K
        8237.0Kbp
        66.4Mbp
        bc2122_select_contigs_size1000
        232.0Kbp
        0.1K
        8223.6Kbp
        210.9Mbp
        bc2123_select_contigs_size1000
        3909.4Kbp
        0.0K
        8224.0Kbp
        64.9Mbp
        bc2124_select_contigs_size1000
        191.6Kbp
        0.1K
        8294.3Kbp
        140.9Mbp
        bc2125_select_contigs_size1000
        2300.4Kbp
        0.0K
        6917.0Kbp
        92.6Mbp
        bc2126_select_contigs_size1000
        2022.5Kbp
        0.0K
        8226.3Kbp
        114.6Mbp
        bc2127_select_contigs_size1000
        3820.7Kbp
        0.0K
        9351.0Kbp
        128.9Mbp
        bc2128_select_contigs_size1000
        2109.1Kbp
        0.0K
        8217.1Kbp
        92.4Mbp
        bc2161_select_contigs_size1000
        4346.0Kbp
        0.0K
        8227.5Kbp
        105.9Mbp
        bc2162_select_contigs_size1000
        276.7Kbp
        0.1K
        7823.1Kbp
        181.9Mbp
        bc2163_select_contigs_size1000
        175.0Kbp
        0.0K
        8228.8Kbp
        76.8Mbp
        bc2164_select_contigs_size1000
        351.1Kbp
        0.0K
        5858.1Kbp
        65.2Mbp
        bc2165_select_contigs_size1000
        2802.4Kbp
        0.0K
        8230.3Kbp
        102.4Mbp
        bc2166_select_contigs_size1000
        207.1Kbp
        0.1K
        10953.7Kbp
        154.9Mbp
        bc2167_select_contigs_size1000
        3081.6Kbp
        0.0K
        5617.2Kbp
        66.0Mbp
        bc2168_select_contigs_size1000
        4074.7Kbp
        0.0K
        6909.6Kbp
        40.1Mbp
        bc2169_select_contigs_size1000
        575.3Kbp
        0.0K
        7026.6Kbp
        247.8Mbp
        bc2170_select_contigs_size1000
        244.5Kbp
        0.0K
        6974.4Kbp
        71.0Mbp
        bc2171_select_contigs_size1000
        473.9Kbp
        0.0K
        5792.8Kbp
        133.0Mbp
        bc2172_select_contigs_size1000
        2117.9Kbp
        0.0K
        6917.9Kbp
        79.9Mbp
        bc2173_select_contigs_size1000
        477.2Kbp
        0.0K
        7025.3Kbp
        138.5Mbp
        bc2174_select_contigs_size1000
        4256.8Kbp
        0.0K
        8282.7Kbp
        85.0Mbp
        bc2175_select_contigs_size1000
        648.2Kbp
        0.0K
        1886.7Kbp
        29.4Mbp
        bc2176_select_contigs_size1000
        4075.7Kbp
        0.0K
        6945.4Kbp
        37.8Mbp

        Number of Contigs

        This plot shows the number of contigs found for each assembly, broken down by length.

        Created with MultiQC

        Reads alignment on final assembly

        This section reports reads alignement on contigs.URL: http://www.htslib.orgDOI: 10.1093/bioinformatics/btp352

        Flagstat

        This module parses the output from samtools flagstat

        Created with MultiQC

        Structural annotation

        This section of the report shows structural annotations results. CDS are predicted using Prodigal, rRNA using Barrnap and tRNA using tRNAscan-se.URL: http://www.vicbioinformatics.com/software.prokka.shtmlDOI: 10.1093/bioinformatics/btu153

        Showing 24/24 rows and 6/6 columns.
        Sample NameOrganism# contigs# bases# CDS# rRNA# tRNA
        bc2121
        NA
        644
        66363466
        63063
        107
        484
        bc2122
        NA
        2121
        210922174
        201900
        373
        1543
        bc2123
        NA
        462
        64902627
        59857
        181
        666
        bc2124
        NA
        1456
        140863752
        133496
        211
        785
        bc2125
        NA
        192
        92566542
        82774
        170
        604
        bc2126
        NA
        3039
        114569058
        92439
        6368
        786
        bc2127
        NA
        4546
        128910244
        106747
        3622
        799
        bc2128
        NA
        3085
        92386496
        75479
        4678
        639
        bc2161
        NA
        499
        105928087
        99076
        244
        1097
        bc2162
        NA
        2002
        181866166
        173738
        387
        1754
        bc2163
        NA
        826
        76848011
        74687
        181
        729
        bc2164
        NA
        605
        65247350
        62961
        141
        727
        bc2165
        NA
        795
        102422094
        97048
        207
        1046
        bc2166
        NA
        1351
        154921777
        141895
        312
        1506
        bc2167
        NA
        543
        65950107
        62053
        314
        383
        bc2168
        NA
        264
        40085885
        35615
        68
        259
        bc2169
        NA
        2320
        247830322
        239278
        446
        2526
        bc2170
        NA
        726
        70971502
        68402
        179
        778
        bc2171
        NA
        1066
        133039126
        128156
        271
        1367
        bc2172
        NA
        1275
        79936471
        72143
        501
        625
        bc2173
        NA
        1039
        138506351
        131371
        243
        1462
        bc2174
        NA
        235
        85041923
        74691
        215
        867
        bc2175
        NA
        97
        29356424
        25787
        39
        184
        bc2176
        NA
        80
        37845507
        33334
        74
        231

        This barplot shows the distribution of different types of features found in each contig.

        Prokka can detect different features:

        • CDS
        • rRNA
        • tmRNA
        • tRNA
        • miscRNA
        • signal peptides
        • CRISPR arrays

        This barplot shows you the distribution of these different types of features found in each contig.

        Created with MultiQC

        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        SoftwareVersion
        FastQC (raw)0.12.1

        Bins Counts quality

        Number of bins by quality category, according to MIMAG (Minimum information about a metagenome-assembled genome) standards. "High-quality" refers to genomes with Completeness > 90% and Contamination < 5%. "Medium-quality" for genomes with Completeness > 50% and Contamination < 10%. "Low-quality" for genomes with Completeness < 50%. "High-contamination refers to genomes with Contamination > 10%. Completeness refers to the proportion of presence of universal single-copy “marker” genes within a genome. Single-copy marker genes present multiple times within a recovered genome is used to estimate potential Contamination.

        Created with MultiQC

        Bins Size (bp) quality

        Cumulative length of sequences by quality category (according to the bins quality category in the figure above), according to MIMAG (Minimum information about a metagenome-assembled genome) standards. The "not-binned" part refers to the cumulative length of assemblies contained in unbinned contigs. The x-axis corresponds to the number of sequences (or proportion), the y-axis indicates the samples.

        Created with MultiQC

        Dereplicate bins stats

        Showing 76/76 rows and 8/8 columns.
        genome_idgenome_namecompletenesscontaminationgenome_lengthgenome_N50contig_countsum_numreadssum_meandepth
        bc2121_bin_1
        s__Streptomyces olivaceus
        100.0
        0.0
        8290288.0
        8236992.0
        2.0
        1197571.0
        1255.0
        bc2121_bin_9
        g__Nocardiopsis
        100.0
        0.1
        6193895.0
        6193895.0
        1.0
        33332.0
        43.4
        bc2121_bin_107
        s__Streptomyces sedi
        82.9
        1.2
        5755202.0
        69039.0
        104.0
        15296.0
        18.8
        bc2122_bin_5
        s__Curtobacterium sp005490985
        100.0
        0.1
        3384980.0
        3384980.0
        1.0
        104917.0
        266.4
        bc2122_bin_11
        s__Bacillus velezensis
        100.0
        0.0
        3850925.0
        2028920.0
        2.0
        6068.0
        14.1
        bc2123_bin_15
        s__Pantoea dispersa
        100.0
        0.0
        4824045.0
        4029856.0
        3.0
        158246.0
        309.0
        bc2123_bin_556
        g__Aureimonas
        55.2
        3.9
        3525599.0
        39943.0
        96.0
        6960.0
        14.2
        bc2124_bin_4
        g__Paenibacillus_D
        100.0
        2.6
        8294254.0
        8294254.0
        1.0
        173102.0
        184.2
        bc2124_bin_381
        s__Nocardiopsis eucommiae
        99.9
        1.6
        5987887.0
        1390012.0
        17.0
        9040.0
        13.3
        bc2127_bin_1
        Unclassified
        61.3
        9.3
        3376366.0
        4457.0
        762.0
        891.0
        1.0
        bc2127_bin_4
        s__Bacillus altitudinis
        100.0
        0.0
        4489429.0
        3740568.0
        7.0
        87592.0
        115.5
        bc2127_bin_5
        s__Leifsonia virtsii
        100.0
        0.0
        3780328.0
        3780328.0
        1.0
        18725.0
        37.7
        bc2127_bin_6
        s__Pseudomonas_B sp913774235
        100.0
        0.0
        5277862.0
        5277862.0
        1.0
        76463.0
        106.9
        bc2161_bin_10
        s__Bacillus_A cereus
        100.0
        0.0
        5233164.0
        5233164.0
        1.0
        5543.0
        10.0
        bc2161_bin_28
        g__Bordetella_A
        100.0
        0.7
        5340606.0
        5340606.0
        1.0
        39744.0
        73.8
        bc2161_bin_38
        g__Microbacterium
        99.8
        4.6
        3970143.0
        2263026.0
        4.0
        3975.0
        9.3
        bc2161_bin_75
        s__Cellulosimicrobium funkei
        100.0
        0.4
        4444578.0
        4444578.0
        1.0
        5429.0
        11.4
        bc2161_bin_273
        g__Neorhizobium
        100.0
        0.0
        5630332.0
        3897655.0
        3.0
        90351.0
        161.5
        bc2162_bin_19
        s__Pantoea septica
        100.0
        0.0
        4109129.0
        4109129.0
        1.0
        71779.0
        156.4
        bc2162_bin_52
        s__Streptomyces bacillaris
        100.0
        0.4
        7661519.0
        4370876.0
        3.0
        83019.0
        92.8
        bc2162_bin_99
        s__Fontibacillus timonensis
        95.2
        0.1
        5313106.0
        239601.0
        28.0
        2571.0
        4.3
        bc2162_bin_140
        s__Methylobacterium radiotolerans
        100.0
        0.2
        5922691.0
        5922691.0
        1.0
        36142.0
        49.4
        bc2163_bin_3
        s__Bacillus safensis
        99.4
        0.1
        3623249.0
        1369808.0
        4.0
        2869.0
        7.5
        bc2163_bin_25
        s__Staphylococcus pseudoxylosus
        100.0
        0.0
        2885999.0
        2885999.0
        1.0
        272175.0
        851.0
        bc2164_bin_13
        g__Aliihoeflea
        50.7
        0.1
        1921745.0
        58067.0
        40.0
        592.0
        2.6
        bc2164_bin_51
        g__Advenella
        62.0
        6.7
        2868363.0
        92195.0
        39.0
        6313.0
        18.8
        bc2164_bin_65
        g__Agrococcus
        87.9
        0.2
        3204766.0
        198018.0
        21.0
        2053.0
        5.9
        bc2164_bin_186
        s__Paracoccus alcaliphilus
        100.0
        0.3
        4321360.0
        3353778.0
        5.0
        16295.0
        33.9
        bc2165_bin_12
        s__Stenotrophomonas maltophilia_G
        100.0
        0.2
        4615726.0
        4615726.0
        1.0
        10297.0
        21.2
        bc2165_bin_81
        s__Agrobacterium tumefaciens_B
        100.0
        0.0
        4782608.0
        2802445.0
        2.0
        78331.0
        158.7
        bc2166_bin_10
        s__Paenibacillus xylanexedens_B
        100.0
        0.2
        6678054.0
        6678054.0
        1.0
        7914.0
        10.5
        bc2166_bin_50
        s__Mammaliicoccus sciuri
        100.0
        0.3
        2845076.0
        2845076.0
        1.0
        91862.0
        344.3
        bc2166_bin_92
        g__Pelagibacterium
        88.2
        1.8
        3077047.0
        206007.0
        27.0
        1180.0
        3.8
        bc2166_bin_97
        s__Brevibacterium sediminis
        100.0
        0.2
        4132946.0
        4132946.0
        1.0
        305290.0
        646.6
        bc2166_bin_922
        g__Advenella
        99.8
        2.4
        9424368.0
        206410.0
        73.0
        11279.0
        9.1
        bc2167_bin_11
        s__Dermacoccus nishinomiyaensis
        100.0
        1.4
        3081641.0
        3081641.0
        1.0
        14278.0
        38.4
        bc2167_bin_185
        s__Agrobacterium cavarae
        100.0
        0.4
        5153887.0
        2884117.0
        6.0
        480584.0
        637.0
        bc2169_bin_5
        s__Enterobacter cloacae
        100.0
        0.0
        4810248.0
        4792661.0
        2.0
        16465.0
        29.8
        bc2169_bin_19
        g__Aquamicrobium_A
        100.0
        0.0
        4271679.0
        4271679.0
        1.0
        10583.0
        21.7
        bc2169_bin_20
        g__Pelagibacterium
        99.9
        0.4
        3610009.0
        3610009.0
        1.0
        10576.0
        26.3
        bc2169_bin_28
        g__Microbacterium
        100.0
        0.2
        3773607.0
        3773607.0
        1.0
        7054.0
        16.4
        bc2169_bin_90
        g__Glycomyces
        79.0
        0.1
        3609587.0
        2178884.0
        11.0
        21720.0
        42.9
        bc2169_bin_103
        s__Cumulibacter soli
        93.5
        0.7
        3849589.0
        292962.0
        19.0
        4139.0
        10.3
        bc2169_bin_116
        s__Aureimonas altamirensis
        64.3
        0.9
        3087177.0
        73557.0
        50.0
        1253.0
        3.3
        bc2169_bin_121
        g__Amoebophilus
        98.3
        0.5
        1792314.0
        1792314.0
        1.0
        4046.0
        20.2
        bc2169_bin_128
        s__Luteimonas abyssi
        99.5
        0.8
        3905832.0
        2640334.0
        2.0
        9733.0
        22.1
        bc2169_bin_134
        s__Advenella incenata
        80.6
        0.5
        3434384.0
        175967.0
        24.0
        5265.0
        12.3
        bc2169_bin_158
        g__Bordetella
        100.0
        0.3
        5372283.0
        5372283.0
        1.0
        11097.0
        17.9
        bc2169_bin_159
        s__Glycomyces sp035765105
        99.4
        0.2
        4667271.0
        4667271.0
        1.0
        24890.0
        41.0
        bc2169_bin_162
        s__Achromobacter ruhlandii
        100.0
        0.1
        6380935.0
        6380935.0
        1.0
        43197.0
        66.4
        bc2169_bin_169
        s__Achromobacter dolens
        100.0
        0.1
        6266697.0
        6266697.0
        1.0
        13688.0
        18.7
        bc2169_bin_911
        s__Leucobacter sp020096995
        63.2
        0.1
        2402833.0
        64098.0
        46.0
        841.0
        3.0
        bc2169_bin_963
        s__Nocardioides luteus
        66.1
        3.1
        3351597.0
        42613.0
        80.0
        1960.0
        4.5
        bc2169_bin_1242
        s__Nocardiopsis flavescens
        100.0
        0.0
        6904792.0
        6904792.0
        1.0
        97378.0
        118.6
        bc2169_bin_1265
        g__Sphingobacterium
        75.6
        2.7
        3290443.0
        63632.0
        65.0
        2405.0
        4.7
        bc2169_bin_1405
        g__Pseudactinotalea
        55.4
        4.6
        3506523.0
        35554.0
        103.0
        1440.0
        2.8
        bc2170_bin_18
        s__Streptomyces albidoflavus
        100.0
        0.3
        6974364.0
        6974364.0
        1.0
        406810.0
        511.5
        bc2170_bin_318
        s__Priestia megaterium
        100.0
        0.5
        5199724.0
        5062286.0
        3.0
        117989.0
        217.4
        bc2170_bin_349
        g__Advenella
        100.0
        0.1
        4798333.0
        4778734.0
        2.0
        344998.0
        708.4
        bc2170_bin_406
        s__Paenibacillus polysaccharolyticus
        97.7
        7.9
        16633353.0
        43978.0
        394.0
        63700.0
        28.5
        bc2171_bin_4
        g__Advenella
        100.0
        0.4
        4650029.0
        4650029.0
        1.0
        11719.0
        26.5
        bc2171_bin_5
        s__Pigmentiphaga kullae
        91.3
        0.8
        5619259.0
        206523.0
        36.0
        1938.0
        3.9
        bc2171_bin_19
        s__Bordetella_A sp002261185
        100.0
        0.1
        5640460.0
        5640460.0
        1.0
        56303.0
        114.0
        bc2171_bin_29
        s__Stenotrophomonas maltophilia_P
        100.0
        0.0
        4181545.0
        4181545.0
        1.0
        140649.0
        327.5
        bc2171_bin_32
        s__Pseudomonas_E berkeleyensis
        100.0
        0.2
        5500779.0
        5500779.0
        1.0
        156778.0
        314.7
        bc2171_bin_36
        s__Brucella pseudogrignonensis
        99.3
        0.0
        4146461.0
        2464969.0
        2.0
        8141.0
        15.1
        bc2172_bin_42
        s__Brucella intermedia
        100.0
        0.5
        4676694.0
        2558761.0
        2.0
        16874.0
        22.1
        bc2172_bin_149
        g__Bordetella_B
        94.6
        0.4
        5821250.0
        181869.0
        73.0
        6334.0
        7.1
        bc2173_bin_4
        s__Pseudomonas_E fulva_B
        100.0
        0.1
        5103136.0
        5103136.0
        1.0
        23774.0
        45.4
        bc2173_bin_45
        g__Aureimonas
        52.6
        1.9
        2454754.0
        58468.0
        45.0
        670.0
        2.6
        bc2173_bin_61
        g__Bordetella_A
        78.0
        0.4
        3935091.0
        221094.0
        27.0
        2324.0
        6.3
        bc2173_bin_86
        s__Olivibacter sp036959255
        100.0
        0.3
        6274207.0
        6274207.0
        1.0
        283399.0
        487.8
        bc2173_bin_121
        g__Brachybacterium
        100.0
        0.1
        4190485.0
        4190485.0
        1.0
        150862.0
        341.3
        bc2173_bin_482
        s__Paracoccus onubensis_A
        92.2
        2.5
        4843498.0
        451359.0
        17.0
        3555.0
        6.7
        bc2173_bin_738
        s__Achromobacter mucicolens
        100.0
        0.1
        5853370.0
        5211448.0
        2.0
        294947.0
        454.9
        bc2174_bin_10
        g__Brevibacterium
        82.2
        0.2
        3527624.0
        541418.0
        12.0
        3401.0
        8.8

        Bins Quality overview

        Quality of bins in terms of completeness and contamination calculated by Checkm2. The points are colored according to their quality, according to the MIMAG standards defined previously (see Bins Counts quality section). Genomes with the best quality (100\% completeness and 0\% contamination) are located in the lower right corner of the graph.

        Created with MultiQC

        Bins Abundances

        Top 30 most abundant genomes (bins) between all samples are shown here. In order to normalize the different library sizes between samples, values are represented as percentages.

        Created with MultiQC

        metagWGS Software Versions

        metagWGS Software Versions are collected at run time from the software output.URL: https://forge.inrae.fr/genotoul-bioinfo/metagwgs

        metagWGS
        v2.5.0
        Nextflow
        v22.04.0
        Python
        v3.10.8
        FastQC
        v0.12.1
        Hifiasm
        v0.13-r308
        Quast
        v5.3.0
        Minimap2
        v2.24-r1122
        Samtools
        v1.15.1
        Concoct
        v1.1.0
        Metabat2
        v2:2.18;
        Maxbin
        v2.2.7
        Binette
        v1.1.2
        dRep
        v3.5.0
        GTDBTK
        v2.4.0
        tRNAscan-SE
        v2.0.11
        Barrnap
        v0.9
        Prodigal
        v2.6.3